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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/38792?offset=110</link>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37211/jbrowse-embeddable-genome-browser-built-completely-with-javascript-and-html5</guid>
	<pubDate>Fri, 29 Jun 2018 09:19:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37211/jbrowse-embeddable-genome-browser-built-completely-with-javascript-and-html5</link>
	<title><![CDATA[JBrowse: Embeddable genome browser built completely with JavaScript and HTML5]]></title>
	<description><![CDATA[JBrowse is a fast, embeddable genome browser built completely with JavaScript and HTML5, with optional run-once data formatting tools written in Perl.

Headline Features:
Fast, smooth scrolling and zooming. Explore your genome with unparalleled speed.
Scales easily to multi-gigabase genomes and deep-coverage sequencing.
Quickly open and view data files on your computer without uploading them to any server.
Supports GFF3, BED, FASTA, Wiggle, BigWig, BAM, VCF (with either .tbi or .idx index), REST, and more.  BAM, BigBed, BigWig, and VCF data are displayed directly from chunks of the compressed binary files, no conversion needed.
Includes an optional “faceted” track selector (see demo) suitable for large installations with thousands of tracks.
Very light server resource requirements. In fact, JBrowse has no back-end server code, just tools for formatting data files to be read directly over HTTP. Serve huge datasets from a single low-cost cloud instance.
Can run as a stand-alone app on OSX and Windows using the Electron platform
Highly extensible plugin architecture, with a large plugin registry of existing examples here https://gmod.github.io/jbrowse-registry

https://jbrowse.org/<p>Address of the bookmark: <a href="https://github.com/GMOD/jbrowse" rel="nofollow">https://github.com/GMOD/jbrowse</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37650/p-rna-scaffolder-a-fast-and-accurate-genome-scaffolder-using-paired-end-rna-sequencing-reads</guid>
	<pubDate>Fri, 07 Sep 2018 05:19:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37650/p-rna-scaffolder-a-fast-and-accurate-genome-scaffolder-using-paired-end-rna-sequencing-reads</link>
	<title><![CDATA[P_RNA_scaffolder: a fast and accurate genome scaffolder using paired-end RNA-sequencing reads]]></title>
	<description><![CDATA[<p><span>P_RNA_scaffolder is a novel scaffolding tool using Pair-end RNA-seq to scaffold genome fragments. The method is suitable for most genomes. The program could utilize Illumina Paired-end RNA-sequencing reads from target speciesies. Our method provides another practical alternative to existing mate-pair_based approaches or other Protein-based approaches (for instance,&nbsp;</span><a href="http://www.fishbrowser.org/software/PEP_scaffolder/">PEP_scaffolder&nbsp;</a><span>) for scaffolding genome sequences. The most important feature of this method is to improve the completeness of gene regions and long-coding gene regions (for instance,&nbsp;</span><a href="http://circrna.org/">circRNA</a><span>).</span></p><p>Address of the bookmark: <a href="http://www.fishbrowser.org/software/P_RNA_scaffolder/#" rel="nofollow">http://www.fishbrowser.org/software/P_RNA_scaffolder/#</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/37959/rainbow-an-integrated-tool-for-efficient-clustering-and-assembling-rad-seq-reads</guid>
	<pubDate>Fri, 19 Oct 2018 08:23:42 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/37959/rainbow-an-integrated-tool-for-efficient-clustering-and-assembling-rad-seq-reads</link>
	<title><![CDATA[Rainbow: an integrated tool for efficient clustering and assembling RAD-seq reads]]></title>
	<description><![CDATA[<p><span>Rainbow is developed to provide an ultra-fast and memory-efficient solution to clustering and assembling short reads produced by RAD-seq. First, Rainbow clusters reads using a spaced seed method. Then, Rainbow implements a heterozygote calling like strategy to divide potential groups into haplotypes in a top&ndash;down manner. And along a guided tree, it iteratively merges sibling leaves in a bottom&ndash;up manner if they are similar enough. Here, the similarity is defined by comparing the 2nd reads of a RAD segment. This approach tries to collapse heterozygote while discriminate repetitive sequences. At last, Rainbow uses a greedy algorithm to locally assemble merged reads into contigs. Rainbow not only outputs the optimal but also suboptimal assembly results. Based on simulation and a real guppy RAD-seq data, we show that Rainbow is more competent than the other tools in dealing with RAD-seq data</span></p><p>Address of the bookmark: <a href="https://sourceforge.net/projects/bio-rainbow/files/" rel="nofollow">https://sourceforge.net/projects/bio-rainbow/files/</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/39671/flye-fast-and-accurate-de-novo-assembler-for-single-molecule-sequencing-reads</guid>
	<pubDate>Sat, 06 Jul 2019 03:48:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/39671/flye-fast-and-accurate-de-novo-assembler-for-single-molecule-sequencing-reads</link>
	<title><![CDATA[Flye: Fast and accurate de novo assembler for single molecule sequencing reads]]></title>
	<description><![CDATA[<p><span>Flye is a de novo assembler for single molecule sequencing reads, such as those produced by PacBio and Oxford Nanopore Technologies. It is designed for a wide range of datasets, from small bacterial projects to large mammalian-scale assemblies. The package represents a complete pipeline: it takes raw PB / ONT reads as input and outputs polished contigs. Flye also includes a special mode for metagenome assembly.</span></p><p>Address of the bookmark: <a href="https://github.com/fenderglass/Flye" rel="nofollow">https://github.com/fenderglass/Flye</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/41030/slr-superscaffolder-a-scaffold-assemble-pipeline-for-stlfr-reads</guid>
	<pubDate>Fri, 14 Feb 2020 14:23:30 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/41030/slr-superscaffolder-a-scaffold-assemble-pipeline-for-stlfr-reads</link>
	<title><![CDATA[SLR-superscaffolder: A scaffold assemble pipeline for stLFR reads.]]></title>
	<description><![CDATA[<p>This is a scaffold assembler designed for stLFR reads[1]. It uses the link-reads information from stLFR reads to assemble contigs to scaffolds.</p>
<p>Here is an illustration of this pipeline:</p>
<p>&nbsp;<img src="https://github.com/BGI-Qingdao/SLR-superscaffolder/raw/master/image.png" alt="image" style="border: 0px;"></p><p>Address of the bookmark: <a href="https://github.com/BGI-Qingdao/SLR-superscaffolder" rel="nofollow">https://github.com/BGI-Qingdao/SLR-superscaffolder</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42132/squeezemeta-a-fully-automated-metagenomics-pipeline-from-reads-to-bins</guid>
	<pubDate>Mon, 17 Aug 2020 05:25:10 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42132/squeezemeta-a-fully-automated-metagenomics-pipeline-from-reads-to-bins</link>
	<title><![CDATA[SqueezeMeta: a fully automated metagenomics pipeline, from reads to bins]]></title>
	<description><![CDATA[<p>SqueezeMeta is a full automatic pipeline for metagenomics/metatranscriptomics, covering all steps of the analysis. SqueezeMeta includes multi-metagenome support allowing the co-assembly of related metagenomes and the retrieval of individual genomes via binning procedures. Thus, SqueezeMeta features several unique characteristics:</p>
<ol>
<li>Co-assembly procedure with read mapping for estimation of the abundances of genes in each metagenome</li>
<li>Co-assembly of a large number of metagenomes via merging of individual metagenomes</li>
<li>Includes binning and bin checking, for retrieving individual genomes</li>
<li>The results are stored in a database, where they can be easily exported and shared, and can be inspected anywhere using a web interface.</li>
<li>Internal checks for the assembly and binning steps inform about the consistency of contigs and bins, allowing to spot potential chimeras.</li>
<li>Metatranscriptomic support via mapping of cDNA reads against reference metagenomes</li>
</ol><p>Address of the bookmark: <a href="https://github.com/jtamames/SqueezeMeta" rel="nofollow">https://github.com/jtamames/SqueezeMeta</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42946/aligngraph2-similar-genome-assisted-reassembly-pipeline-for-pacbio-long-reads</guid>
	<pubDate>Sun, 14 Mar 2021 09:42:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42946/aligngraph2-similar-genome-assisted-reassembly-pipeline-for-pacbio-long-reads</link>
	<title><![CDATA[AlignGraph2: similar genome-assisted reassembly pipeline for PacBio long reads]]></title>
	<description><![CDATA[<p><span>AlignGraph2 is the second version of&nbsp;</span><a href="https://github.com/baoe/AlignGraph">AlignGraph</a><span>&nbsp;for PacBio long reads. It extends and refines contigs assembled from the long reads with a published genome similar to the sequencing genome.</span></p>
<p><span>More at&nbsp;https://academic.oup.com/bib/advance-article-abstract/doi/10.1093/bib/bbab022/6146772</span></p><p>Address of the bookmark: <a href="https://github.com/huangs001/AlignGraph2" rel="nofollow">https://github.com/huangs001/AlignGraph2</a></p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/44171/hairsplitter-assembling-long-reads-in-an-unknown-number-of-haplotypes</guid>
	<pubDate>Wed, 07 Dec 2022 00:13:40 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/44171/hairsplitter-assembling-long-reads-in-an-unknown-number-of-haplotypes</link>
	<title><![CDATA[HairSplitter: assembling long reads in an unknown number of haplotypes]]></title>
	<description><![CDATA[<p>Pros and cons of HairSplitter Limitations of HairSplitter:</p>
<p>Not very fast: it re-polishes the whole assembly&nbsp;</p>
<p>Limited in the number of haplotypes</p>
<p>Strengths of HairSplitter:</p>
<p>Very modular, can be used with any assembler</p>
<p>Naive: makes no assumption on ploidy, parameter-free</p>
<p>Safe: won&rsquo;t artificially duplicate contigs</p>
<p>&nbsp;</p>
<p>HairSplitter splits collapsed assemblies from &ldquo;draft&rdquo; assemblies obtained by any means</p>
<p>HairSplitter can recover haplotypes and distinguish repeated elements</p>
<p>Only needs sequencing reads, potentially error-prone</p>
<p>HairSplitter splits collapsed assemblies from &ldquo;draft&rdquo; assemblies obtained by any means</p>
<p>HairSplitter can recover haplotypes and distinguish repeated elements</p>
<p>Only needs sequencing reads, potentially error-prone</p>
<p>Not really available yet (github.com/RolandFaure/HairSplitter)</p>
<p>https://hal.archives-ouvertes.fr/hal-03864075/file/RolandFaure_presentation_SeqBIM_2022.pdf</p><p>Address of the bookmark: <a href="https://hal.archives-ouvertes.fr/hal-03817928/document" rel="nofollow">https://hal.archives-ouvertes.fr/hal-03817928/document</a></p>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/26975/trimmomatic-a-flexible-read-trimming-tool-for-illumina-ngs-data</guid>
	<pubDate>Fri, 15 Apr 2016 05:58:53 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/26975/trimmomatic-a-flexible-read-trimming-tool-for-illumina-ngs-data</link>
	<title><![CDATA[Trimmomatic: A flexible read trimming tool for Illumina NGS data]]></title>
	<description><![CDATA[<h4>Paired End:</h4>
<p><code>java -jar trimmomatic-0.35.jar PE -phred33 input_forward.fq.gz input_reverse.fq.gz output_forward_paired.fq.gz output_forward_unpaired.fq.gz output_reverse_paired.fq.gz output_reverse_unpaired.fq.gz ILLUMINACLIP:TruSeq3-PE.fa:2:30:10 LEADING:3 TRAILING:3 SLIDINGWINDOW:4:15 MINLEN:36</code></p>
<p>This will perform the following:</p>
<ul>
<li>Remove adapters (ILLUMINACLIP:TruSeq3-PE.fa:2:30:10)</li>
<li>Remove leading low quality or N bases (below quality 3) (LEADING:3)</li>
<li>Remove trailing low quality or N bases (below quality 3) (TRAILING:3)</li>
<li>Scan the read with a 4-base wide sliding window, cutting when the average quality per base drops below 15 (SLIDINGWINDOW:4:15)</li>
<li>Drop reads below the 36 bases long (MINLEN:36)</li>
</ul>
<p>More at http://www.usadellab.org/cms/?page=trimmomatic</p><p>Address of the bookmark: <a href="http://www.usadellab.org/cms/?page=trimmomatic" rel="nofollow">http://www.usadellab.org/cms/?page=trimmomatic</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/27440/stampy</guid>
	<pubDate>Fri, 20 May 2016 19:13:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/27440/stampy</link>
	<title><![CDATA[Stampy]]></title>
	<description><![CDATA[<p><strong>Stampy&nbsp;</strong><span>is a package for the mapping of short reads from illumina sequencing machines onto a reference genome. It's recommended for most workflows, including those for genomic resequencing, RNA-Seq and Chip-seq. Stampy excels in the mapping of reads containing that contain sequence variation relative to the reference, in particular for those containing insertions or deletions.</span></p><p>Address of the bookmark: <a href="http://www.well.ox.ac.uk/project-stampy" rel="nofollow">http://www.well.ox.ac.uk/project-stampy</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
</item>

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